Indicators for Self-assessment of Human Practices in Homes

Manar Amayri

, Helene Haller

, Stephane Ploix

, Frederic Wurtz

and Gilles Debizet

Grenoble Institute of Technology, G-SCOP, France

Pacte, Laboratoire de Sciences Socaies, France

Grenoble Institute of Technology, G2ELab, France

Keywords:

Building Performance, Energy, Human Behavior, Indicators.

Abstract:

Usage indicators are proposed in smart buildings in order to analyze occupant behavior towards energy usage.

Indicators are a means of communication to interact with occupants of a living area so they can make informed

decisions regarding their everyday customs and uses. Through them, occupants will be able to compare and

challenge themselves with others or with their past results. Moreover, occupants will be able to understand

the consequences and effects of their energy behavior and learn how to improve it without degrading their

comfort. Heat ﬂow through door/window indicators (heat losses), and dishwasher indicator have been cal-

culated and discussed in an apartment context. There were 70 heterogeneous sensors previously installed to

gather the information needed. These indicators have been evaluated by considering three conditions: mea-

surable/calculable, understandable and comparable/challengeable between different houses or users. Studying

and measuring different indicators give a sort of energy performance of a building, which in turn helps to

improve automated building management tools.

1 INTRODUCTION

The residential sector is playing an essential role in

the context of overall energy consumption. Indeed,

the limit is not certain but the amount of energy us-

age can be minimized up to a certain extent so as to

balance the energy ﬂow. Hence, it can be said that the

energy efﬁciency is an important challenge in today’s

area of building and automation system, but how one

can minimize the energy consumption and how hu-

man behavior plays a vital role in regards to the en-

ergy consumption of the living area?

Today, there are numerous services and tools

available which provide the exact information about

the amount of energy being used by any particular

appliance or service in a living area. However, the

biggest questions coming out of those statistics is that:

whether one can improve energy efﬁciency using less

energy for the same service or not. How human be-

havior is playing a vital role considering the main fo-

cus is to reduce the overall energy consumption while

keeping the comfort level.

Energy savings depend on the conscious action of

the inhabitants, which is not likely to be constant over

time. Thus, lots of work have been focused on de-

veloping energy intelligent buildings by integrating

occupant activity and behavior as a key element for

building management systems with which the build-

ings can automatically save energy. For this purpose,

indicators are an important part to help to build bet-

ter automation building management tools but also to

show a visual use of energy performance to the in-

habitants coming from their own daily behavior on

the building. In order to understand the energy Us-

age and act in accordance with that, some indicators

are required, which can estimate the cause and ef-

fect of the particular action in regards to the overall

energy consumption.They aimed at synthesizing sev-

eral data, which occupants would not be able to un-

derstand separately and make it intelligible. Indica-

tors are divided or categorize depending on what they

measure, there are: (1) technical indicator: showing

the performance of the building, (2) usage indicators:

showing the amount of energy used or wasted, which

is directly or indirectly related to occupant’s actions

on a daily basis (cost is also included here). Another

type of indicator is (3) comfort indicators: like ther-

mal or air quality comfort. They show how the ac-

tions of the occupants affect the comfort levels inside

the house or building.

This paper tackles this issue by proposing and an-

alyzing some usage and comfort indicators. Section 2

presents a state of the art about indicators and building

performance. Section 3 deals with energy consump-

tion practices factors. Section 4 proposed different

indicators. Section 5 focuses on data collection and

116

Amayri, M., Haller, H., Ploix, S., Wurtz, F. and Debizet, G.

Indicators for Self-assessment of Human Practices in Homes.

DOI: 10.5220/0007716801160122

In Proceedings of the 8th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS 2019), pages 116-122

ISBN: 978-989-758-373-5

apartment case study. Section 6 results of heat ﬂow

and dishwasher indicators.

2 STATE OF THE ART

Following the electricity trends and the design of the

new smart buildings, several solutions were devel-

oped in regards to saving the energy consumption in-

side a building. (Nguyen, 2013a) concluded that

there is a possibility of 58% saving on energy for

lighting and 10-40% for HVAC system. Some other

studies like (Georgievski and Degeler, 2012) which

were conducted in the commercial sector showed an

average economic saving of about 35% by presenting

an approach based on measuring energy consumption

on individual user activity and service.

Some appliances and services are very dynamic

and uncontrollable, (Nguyen, 2013b) illustrates the

different application of information feedback method

in order to save energy consumption in a living

area. He presented the ﬁndings of a UK based ﬁeld

study involving 44 households considering domestic

cooking: he compares the effectiveness of provid-

ing paper-based energy-use/saving information with

electronic feedback of energy-consumption via ECIs

(Energy Consumption Indicators) designed speciﬁ-

cally for this investigation. Twelve Control Group

households were monitored for a period of at least

12 months and it revealed an average daily consump-

tion for electric cooking of 1.30 kWh. Subsequently

across a minimum monitoring period of 2 months, 14

out of 44 households achieved energy savings greater

than 10% and six of these achieved savings of greater

than 20%. The average reduction for households em-

ploying an ECI was 15%, whereas that given an-

tecedent information alone reduced their electricity

consumption, on average, by only 3%. The associ-

ated behavioral changes and the importance of pro-

viding regular feedback during use were identiﬁed by

them. The study (ref, 2017) illustrates that build-

ing energy use is mainly inﬂuenced by different fac-

tors: climate, building structure, building services and

energy systems, building operation and maintenance,

occupants’ activities and behavior, and indoor envi-

ronmental quality. Among these factors, the last three

ones are human-related factors which can have an in-

ﬂuence as signiﬁcant as the ﬁrst three.

In (M. G. Ellis and Gigawatts, 2009) represent

that now most new appliances have designed to uti-

lize up to 40% less electricity which is not quite

enough to insert them into the class of smart appli-

ances. One feature of smart appliances is that they

are designed to be able to measure their own power

consumptions and it uses this data to conserve elec-

tricity and money, in addition being programmable.

However, there are some home automation solutions

available to use wireless technology, as well as ex-

isting wiring’s home to be connected and automated

appliances.

The road toward energy efﬁciency is reached, in

part, with the implementation of the smart appliances

and smart meters, and the need of indicators become

somewhat very important to collect and give form to

all human behaviors which directly or indirectly affect

the usage of the energy. Indicators play a big role to

reach the European Union target of 2020 (ref, 2018a).

Knowing all the details about the energy consumption

is not always enough, to make sure that the occupant

is going to reduce energy consumption. Therefore, it

is also required to make a link between all the waste

towards the occupant behavior and represent it in such

a way that an occupant can understand it and act in

accordance with. The study of this paperwork to in-

volve the idea of such an indicator and a way how

can a better indicator be designed keeping more prag-

matic towards the occupant approach as a sustainable

solution.

3 ENERGY CONSUMPTION

PRACTICES FACTORS

Human behaviors regarding energy consumption are

complex but it is possible to grasp some factors about

energy consumption behaviors and how to change be-

haviors on a long-term basis. First, people often act

differently as they say they will, but they feel some

discomfort from this situation. It is called “cogni-

tive dissonance” (L, 1957). People also tend to sus-

tain their behavioral changes when they get commit-

ted in public. The induced hypocrisy paradigm (Is-

abella Gaetani, 2010) is based on these observations:

the mechanism aims to artiﬁcially recreate a cogni-

tive dissonance situation. Once a person gets com-

mitted, it is important to recall his commitment every

time it is transgressed. The work in (Isabella Gae-

tani, 2010) also underlines the importance of belong-

ing to a group, i.e. a community. Besides, people

are reluctant to change. Imposing a change to peo-

ple is badly abided. To get a change in a behav-

ior, you have to obtain the will of people and make

them feel like nothing is demanded (Isabella Gae-

tani, 2010). In other words, you have to ﬁnd a way to

involve them in decision making. Moreover, under-

standing the nature of practices is a way to make sure

that the changes will be sustainable. Practices are at

the junctions of three elements: a meaning, a material

Indicators for Self-assessment of Human Practices in Homes

117

dimension and some competences (Shove E., 2012).

Changing a practice should take simultaneously into

account these three elements. Therefore, the creation

of indicators must rely on a meaning shared with the

users, being supported by a device or an application

easily understandable and useable, and they must not

require expertise on energy efﬁciency because it can’t

be assumed that targeted users of indicators know a lot

about energy. In addition, energy consumption prac-

tices respond to “logic of action”, i.e. all the actions

carried out to achieve an ideal. This ideal is based on

some sociological norms and values. Several logic ac-

tions have been identiﬁed to highlight the interactions

between a device (which goal is energy efﬁciency)

and an user (S, 2015). They can be easily transposed

to the creation of an indicator:

• comfort at home

• seek for fun in the use of technologies

• desire to control the housing and life

• interest for every element related to energy

• economical behavior

• ecological behavior

But energy efﬁciency is not a goal that only con-

cerns inhabitants. In fact, this problem affects differ-

ent publics: consumers of course, but also citizens,

energy operators, local authorities. These different

publics do not meet the same goals. Indicators must

embrace this complexity to be more accurate. Feed-

back must be taken into account as another dimension

related indicators requirement. Delivering informa-

tion about energy consumption is not enough to lead

to behavior changes. Consumers need accurate infor-

mation to understand how they consume. Two ques-

tions arise from this assessment:

• what should be the temporality covered by feed-

backs?

• what should be the spatiality covered by feed-

backs?

These questions are dealing with the rapidity

and precision for information delivery about energy

consumption to obtain commitment and long-term

changes.

Firstly, indicators should provoke desire to act, by

mobilizing social norms and values that guide the en-

ergy behaviors of users. Secondly, users must have

the capacity to react to the messages delivered by the

indicators. As a consequence, energy efﬁcient appli-

ances linked to sensors and indicators have to be easy

to use. Thirdly, delivered messages by the indicators

have to be understandable by non-expert users.

Regarding the temporality, it depends on the na-

ture of the indicator itself and the glimpse the user

would like to get. It can go from one second to one

year. Regarding the spatiality, it has been underlined

earlier the importance of being part of a group to

achieve a sustainable change. That’s why it is also

recommended to develop meaningful and shareable

indicators. Using comparison can help people to po-

sition themselves and strengthen their commitment.

From the energy point of view, the evolution of smart

grid to the smart meter and smart appliances there are

many ways to measure the consumption of electric-

ity, with the help of these measurements, more new

challenges come into consideration.

4 PROPOSED USAGE

INDICATORS

Improvements in the energy performance of a build-

ing cannot be achieved at the expense of the comfort

of building occupants. Consequently, it is necessary

to measure the comfort levels within the building in

order to ensure that primarily the occupants of a build-

ing are comfortable and also to ensure that all legal

requirements related to comfort are satisﬁed. Thus,

these indicators are designed to inform both building

managers and building users on the impact of their be-

havior on the performance of the building. Below are

the proposed indicators related to usage.

4.1 Heat-ﬂow Indicator

This indicator is a usage indicator for the energy

loss (turn on the heater/air conditioner, open/close a

door/window). The ﬁrst step is to link this indicator

with the occupant’s actions in the house. What are

the actions responsible for the loss of heat produced

in the house, and what actions must be taken in order

to avoid it and have a good indicator of reading?

4.1.1 Heat-ﬂow Indicator through the Window

In a room, there are 2 main ways for the heat to be

wasted, through the window or through the door. Be-

fore calculating heat ﬂow indicator through these 2

factors, there are 3 conditions that must be met to be

a waste:

1. heater or air conditioning systems must be on.

2. window must be opened during the calculation

time.

3. CO2 concentration should be below 1000 ppm, as

stated in (ref, 1969) (if the CO2 levels are higher

SMARTGREENS 2019 - 8th International Conference on Smart Cities and Green ICT Systems

118

than the calculation of heat loss is not done that

because opening the window was necessary to

freshen the air quality)

Finally, the indicator is calculated as a difference

in temperature between outdoor and indoor tempera-

ture. (i.e. number of waste degrees) The proposal for-

mula of the algorithm is presented as such equation

pos(T

− T

out

)window

position

threshold

(co

)dtheater

status

(1)

This formula is for calculation of heat ﬂow during

winter, when there is positive heat ﬂow through the

window to outdoor when it is too cold outdoors. Vice

versa during summer the calculation is done when

there is positive heat ﬂow through the window from

outdoor when it is too hot outdoor, equation 2.

pos(T

− T

out

)window

position

threshold(co

)dtconditioner

status

(2)

4.1.2 Heat-ﬂow Indicator through the Door

Heat-ﬂow though the door is the same as the one for

the window with the only exceptions being the posi-

tion of the door opening and the heat ﬂows not outside

but on the corridor, equation 3 and equation 4.

pos(T

− T

corridor

)door position

threshold(co

)dtheater

status

(3)

pos(T

− T

corridor

)door position

threshold(co

)dconditioner

status

(4)

Thus, this indicator provides data on the differ-

ence in interior and corridor temperatures for time pe-

riods, where the door should be opened.

1. heater must be ON, otherwise, there is no energy

lost from heating.

2. window must be opened during the calculation

time.

4.2 Dishwasher Machine Indicators

Since appliances are responsible for around 20% of

the total energy consumption (ref, 2018b), it makes

sense that the usage of these appliances should be

focused. The ﬁrst step is to link their consump-

tion with the occupant’s interaction with these appli-

ances. Dishwasher machine data has been investi-

gated, where two indicators have been extracted from

their recorded power consumption:

1. dishwasher machine average consumption during

each cycle.

2. number of cycles (daily, weekly,....).

5 RESULTS

5.1 Apartment Case Study

A residential apartment in Grenoble, France has been

investigated, which is considered as a multi-zone ap-

plication with lots of sensors and different activities.

The setup for the sensor network includes 70 sensors:

• temperature sensor in each room.

• motion sensor in each room.

• windows contact sensor in each room.

• doors contact sensor in each room.

• power consumption sensors in the kitchen (i.e,

dishwasher, clothwasher, ...).

• appliances power consumption sensors in each

room.

• humidity sensor in each room.

• uminosity sensor in each room.

It consists of two bedrooms, a common room, a

kitchen, an ofﬁce, a separate bathroom, and toilets.

The doors and windows are equipped with contact

sensors providing binary numbers related to the state

of the doors or windows i.e. 1 for open and 0 for

closed. Only the contact sensors give values as binary

state whereas the rest of the sensors measure their re-

spective variables to the extent of the intensity i.e. the

luminosity in the kitchen.

• washing machine average consumption for each

machine cycle (for all users or per user) indicator.

• dishwasher machine average consumption for

each machine cycle (for all users or per user) in-

dicator, where a cycle is a one working phase of

the dishwasher machine.

• a number of cycles indicator (i.e washing ma-

chine, dishwasher machine...).

• heat ﬂoat(loss of heat) through a door/window in-

dicator.

• CO2 average concentration indicator.

• comfort ICONE indicator.

• fridge usage indicator.

In this paper the discussion is focused on two types of

indicators:

Indicators for Self-assessment of Human Practices in Homes

119

Figure 1: Heat ﬂow through window, overview of temperature differencesy.

1. heat-ﬂow indicator (through door/window).

2. dishwasher indicators.

The data coming from the sensors was recorded and

monitored from December 2015 to August 2017 in

the apartment case study, one room is chosen to do

the experiment of indicator calculation (ofﬁce room).

Fig. 1 presents the heat ﬂow indicator in one room

through the window. The blue curve is the indoor tem-

perature, the green is the outdoor one, and in red is the

indicator. Only in 2 instances, there has been a heat

loss or a ﬂow of heat from indoor to outdoor for this

case, which show a good behavior of the user. Fig.

2 presents the heat ﬂow through the door, a different

story can be seen. During the whole winter, there is a

lot of heat ﬂow from the room to the corridor (green

curve), where the door openings. In this case, the dif-

ference between room and corridor temperatures are

highly affected by the heat ﬂow.

Following the objective of indicator design, for

heat ﬂow indicators they can be got 2 pluses for 2

criteria, namely understandable and comparable, but

only one plus for the measurable criteria. The reason

for this is because even though it is very easy to Cal-

culate, the information needed (i.e. reading window

and door openings), it’s not common to be installed in

every house or building. But for the other 2 criteria, it

is easily understandable and comparable.

• measurable/ calculable + (1 plus)

• understandable ++ (2 pluses)

• comparable/ challengeable ++ (2 pluses)

Fig. 3 shows the weekly consumption of the dish-

washer machine for 3 different houses, this value will

be more interesting for the end user if it is presented

as average consumption each cycle (see Fig. 4(b)).

In order to compare the usage from different dish-

washer machines, we must link their usage with a

user’s activity, in this case, the number of cycles used

during the week on average. (see Fig. 4(a)) shows

the number of cycles each week for three different

houses A similar conclusion can be done for this in-

dicator, they are easily measurable and calculable, as

well as comparable with different houses. The con-

sumption of the appliances is directly linked with the

number of cycles, which can give the user a simple

and motivated way to be in challenged and to compare

with other users. For example, some challenges can

appear between the greenhouse and the orange one.

Both houses have almost the same number of cycles

(Fig. 4(a)), but the greenhouse has less consumption

compared with the orange one (Fig. 4(a)).

• measurable/ Calculable + (1 plus)

• understandable + + (2 pluses)

• comparable/ Challengeable ++ (2 pluses)

6 CONCLUSION AND FUTURE

WORK

Usage indicators have been discussed in this paper.

Indicators are variables characterized by their values

with a signiﬁcant representation. Indeed, they aimed

SMARTGREENS 2019 - 8th International Conference on Smart Cities and Green ICT Systems

120

Figure 2: Heat ﬂow through door, an overview of temperature differences.

to synthesize different information which occupants

would not be able to understand separately and make

it intelligible.

Among different proposed usage indicators, two

have been discussed in this paper, heat ﬂow through

door/window, and dishwasher indicator, all showed a

quite good presentation to the end user according to 3

criteria: measurable, understandable and comparable

between different houses or users.

Depending on the responsibility of the occupants

in a house, and regarding the openings and closings of

the window or door, it was easy to measure and link

behavior with the loss of heating as a result. This us-

age indicator (called Heat-ﬂow indicator) shows good

results, it is very understandable and comparable and

can be applied with ease to different house settings.

Continuous work can also be done in identify-

ing and designing new indicators as well. Probably,

identifying new user’s activities or even linking dif-

ferent indicators with each other. More indicators are

however required especially indicators related to the

use of high energy consuming appliances and comfort

levels within a building. These are especially neces-

sary in order to avoid achieving high energy perfor-

mance at the expense of the comfort of building occu-

pants.

In terms of the future scope of this research, it

would be very interesting to make a small-scale exper-

iment with some experimental reference values, just

to know if it can work for the occupants keeping the

level of comfort constant. A survey could also be very

interesting to investigate or judge the user on the basis

of reference values. Further, in order to know the efﬁ-

ciency and feasibility of the proposed indicator a large

scale experimentation could also be done referring to

it as magic to save the energy.

Develop a graphical user interface solution for

better presenting the indicators to the end user. Fi-

nally, an important point should be investigated and

develop the experimental evaluation. There is a lack

of methodological guidance in the information visu-

alization literature on how to do so. The problem is

two-fold: (1) objective measures are not enough to

capture the quality of a decision, given that “ﬁnding a

good compromise” is by essence, subjective. Subjec-

tive measures such as self- reported satisfaction are

useful but may be unreliable. (2) there is a lack of

clear references for identifying an appropriate base-

line for comparative assessment.

ACKNOWLEDGMENT

This work is supported by the French National Re-

search Agency in the framework of the ” Investisse-

ments d'avenir” program (ANR-15-IDEX-02)( IN-

VOVED and Eco-SESA, Comepos projects).

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